My data set is of shape
(1249, 228). Most of the entries are zero and other are integers like 1,2,5,10,20 etc. I want to transform this set for the input into LSTM. But when I am applying
MinMaxScaler. It is giving the following error:
load the dataset:
dataset1 = pd.read_csv('g:/hello.csv', engine='python') dataset1= dataset1.drop('packages', axis=1) dataset1 = dataset1.astype('float32')
normalizing the set
scaler = MinMaxScaler(feature_range=(0, 1)) dataset1 = scaler.fit_transform(dataset1)
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
How can I transform this data set according to the input in LSTM.